The EOSC-hub project creates the integration and management system of the future European Open Science Cloud that delivers a catalogue of services, software and data from the EGI Federation, EUDAT CDI, INDIGO-DataCloud and major research e-infrastructures. This integration and management system (the Hub) builds on mature processes, policies and tools from the leading European federated e-Infrastructures to cover the whole life-cycle of services, from planning to delivery. The Hub aggregates services from local, regional and national e-Infrastructures in Europe, Africa, Asia, Canada and South America. The Hub acts as a single contact point for researchers and innovators to discover, access, use and reuse a broad spectrum of resources for advanced data-driven research. Through the virtual access mechanism, more scientific communities and users have access to services supporting their scientific discovery and collaboration across disciplinary and geographical boundaries. The project also improves skills and knowledge among researchers and service operators by delivering specialised trainings and by establishing competence centres to co-create solutions with the users. In the area of engagement with the private sector, the project creates a Joint Digital Innovation Hub that stimulates an ecosystem of industry/SMEs, service providers and researchers to support business pilots, market take-up and commercial boost strategies. EOSC-hub builds on existing technology already at TRL 8 and addresses the need for interoperability by promoting the adoption of open standards and protocols. By mobilizing e-Infrastructures comprising more than 300 data centres worldwide and 18 pan-European infrastructures, this project is a ground-breaking milestone for the implementation of the European Open Science Cloud.

Simulations based on the numerical solution of Partial Differential Equations (PDEs) are nowadays customarily being applied for the design of industrial products and plants, in several branches of the Computer Aided Engineering (CAE), such as thermodynamics, fluid dynamics, structural mechanics. The improvement of the mathematical modeling tools and the availability of computing power have dramatically enhanced the accuracy of computer based simulations, and hence the support they offer to engineering design process. Yet, due to their complexity, in most cases simulations are not fully integrated into the design workflow. Operations as preprocessing, grid generation, setting up and running the simulations, and postprocessing the outputs, require specific skills and are extremely time and resources consuming. For these reasons, design engineers are sometimes resorting to simplified low fidelity models, which are often quantitatively inaccurate. More complex and accurate high fidelity models are only and occasionally considered at the very end of the design cycle, and are usually employed to optimize single components or to provide a final assessment of the overall accuracy of the standard simpler models. In this background, introducing accessible high-fidelity models in a user friendly intermediate environment would represent a strategic asset to facilitate and spread simulation-based design approaches and their benefits for industries in new industrial applications, as already happens for example in automotive or aerospace industry, towards a more efficient resources employment, energy saving and optimized products. The objective of the project is to set up a user friendly high-fidelity simulation platform, based on efficient simulation techniques and standardized automated workflows to be provided as a Simulation-as-a-Service (SaaS) tool, for the design and optimization of industrial furnaces.

Abdominal Aneurysm of the Aorta (AAA) is a degenerative disease of the last segment of the abdominal aorta, representing the 14th leading cause of death for the 60 to 85 year-old age group in US. An estimated 80 million people aged 60 years and older are at risk in Western Europe. To date the most commonly used clinical protocol for surgical acceptance is based on the estimate of AAA diameter. The report prepared for the Agency for Healthcare Research and Quality came to the conclusion that: the annual risk of rupture is 1% or lower for a diameter less than 5.5 cm; the 1-year risk of rupture increases with the aneurysm size; it may exceed 10% in the individuals with diameters above 6 cm. Assessment of AAA rupture risk has long been a topic of interest in clinical research setting. The ability to estimate patient specific probability of AAA rupture can lead to reduced health care costs, adequate and timely patient diagnostic and comfort. Math4AAArisk aims at the realization of a mathematical platform to support clinicians through the following steps: (A1) From medical imaging to sizing and morphological characterization of AAA, (A2) Preliminary risk evaluation, (A3) Computer simulation and enhanced risk assessment, (B1) Automatic surgery planner, (C1) Anonymous data base storage. The proposed mathematical platform yields quantitative physical indicators in real time at the sole request of inputting a few clinical measurements; it is patient adapted, as it integrates with patient’s radiological images, under full control of clinicians; it is aimed at improving the diagnostic analysis and possibly the surgical planning. We wish to establish the viability for a market exploitation of the math4AAArisk platform and identify possible later stage funding opportunities.